{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,3]],"date-time":"2026-08-03T06:45:08Z","timestamp":1785739508853,"version":"3.56.0"},"reference-count":33,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2022,12,9]],"date-time":"2022-12-09T00:00:00Z","timestamp":1670544000000},"content-version":"vor","delay-in-days":342,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002347","name":"Bundesministerium f\u00fcr Bildung und Forschung","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100002347","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The scientific literature continues to grow at an ever-increasing rate. Considering that thousands of new articles are published every week, it is obvious how challenging it is to keep up with newly published literature on a regular basis. Using a recommender system that improves the user experience in the online environment can be a solution to this problem. In the present study, we aimed to develop a web-based article recommender service, called Emati. Since the data are text-based by nature and we wanted our system to be independent of the number of users, a content-based approach has been adopted in this study. A supervised machine learning model has been proposed to generate article recommendations. Two different supervised learning approaches, namely the na\u00efve Bayes model with Term Frequency-Inverse Document Frequency (TF-IDF) vectorizer and the state-of-the-art language model bidirectional encoder representations from transformers (BERT), have been implemented. In the first one, a list of documents is converted into TF-IDF\u2013weighted features and fed into a classifier to distinguish relevant articles from irrelevant ones. Multinomial na\u00efve Bayes algorithm is used as a classifier since, along with the class label, it also gives the probability that the input belongs to this class. The second approach is based on fine-tuning the pretrained state-of-the-art language model BERT for the text classification task. Emati provides a weekly updated list of article recommendations and presents it to the user, sorted by probability scores. New article recommendations are also sent to users\u2019 email addresses on a weekly basis. Additionally, Emati has a personalized search feature to search online services\u2019 (such as PubMed and arXiv) content and have the results sorted by the user\u2019s classifier.<\/jats:p>\n               <jats:p>Database URL: https:\/\/emati.biotec.tu-dresden.de<\/jats:p>","DOI":"10.1093\/database\/baac104","type":"journal-article","created":{"date-parts":[[2022,12,9]],"date-time":"2022-12-09T11:18:13Z","timestamp":1670584693000},"source":"Crossref","is-referenced-by-count":7,"title":["Emati: a recommender system for biomedical literature based on supervised learning"],"prefix":"10.1093","volume":"2022","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6954-4928","authenticated-orcid":false,"given":"\u00d6zge","family":"Kart","sequence":"first","affiliation":[{"name":"Biotechnology Center (BIOTEC), Center for Molecular and Cellular Bioengineering (CMCB), Technische Universit\u00e4t Dresden , Tatzberg 47-49, Dresden 01307, Germany"},{"name":"Department of Computer Engineering, Dokuz Eyl\u00fcl University , Tinaztepe Campus, Buca 35160 Izmir, Turkey"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandre","family":"Mestiashvili","sequence":"additional","affiliation":[{"name":"Biotechnology Center (BIOTEC), Center for Molecular and Cellular Bioengineering (CMCB), Technische Universit\u00e4t Dresden , Tatzberg 47-49, Dresden 01307, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kurt","family":"Lachmann","sequence":"additional","affiliation":[{"name":"Biotechnology Center (BIOTEC), Center for Molecular and Cellular Bioengineering (CMCB), Technische Universit\u00e4t Dresden , Tatzberg 47-49, Dresden 01307, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Richard","family":"Kwasnicki","sequence":"additional","affiliation":[{"name":"Biotechnology Center (BIOTEC), Center for Molecular and Cellular Bioengineering (CMCB), Technische Universit\u00e4t Dresden , Tatzberg 47-49, Dresden 01307, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2848-6949","authenticated-orcid":false,"given":"Michael","family":"Schroeder","sequence":"additional","affiliation":[{"name":"Biotechnology Center (BIOTEC), Center for Molecular and Cellular Bioengineering (CMCB), Technische Universit\u00e4t Dresden , Tatzberg 47-49, Dresden 01307, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,12,9]]},"reference":[{"key":"2022121207571060000_R1","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1007\/s00799-014-0122-2","article-title":"A comprehensive evaluation of scholarly paper recommendation using potential citation papers","volume":"16","author":"Sugiyama","year":"2015","journal-title":"Int. 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